The present invention relates to a noisy speech parameter enhancement method and apparatus that may be used in, for example noise suppression equipment in telephony systems.
A common signal processing problem is the enhancement of a signal from its noisy measurement. This can for example be enhancement of the speech quality in single microphone telephony systems, both conventional and cellular, where the speech is degraded by colored noise, for example car noise in cellular systems.
An often used noise suppression method is based on Kalman filtering, since this method can handle colored noise and has a reasonable numerical complexity. The key reference for Kalman filter based noise suppressors is Reference [1]. However, Kalman filtering is a model based adaptive method, where speech as well as noise are modeled as, for example, autoregressive (AR) processes. Thus, a key issue in Kalman filtering is that the filtering algorithm relies on a set of unknown parameters that have to be estimated. The two most important problems regarding the estimation of the involved parameters are that (i) the speech AR parameters are estimated from degraded speech data, and (ii) the speech data are not stationary. Thus, in order to obtain a Kalman filter output with high audible quality, the accuracy and precision of the estimated parameters is of great importance.